外文原文.pdf

Virtual automatic tool changer of a machining centre with a real-time simulation Y.H. Jeonga, H. Taeb, B.-K. Mincand D.-W. Chod* aSchool of Mechanical Engineering, Yonsei University, Seoul, 120-749, Korea;bCentral R cSchool of Mechanical Engineering, Yonsei University, Seoul, 120-749, Korea; dDepartment of Mechanical Engineering, Pohang University of Science and Technology, Pohang, Kyungbuk, 790-784, Korea (Received 27 June 2007; fi nal version received 13 November 2007) The discrete systems in a machining centre, such as the automatic tool changer and automatic pallet changer, play important roles in improving productivity in machining automation. However, system confi guration and sequential logic programming still require considerable skill and are handled on a case by case basis. A simulation-based verifi cation environment could improve system performance, reduce ramp-up time and cost, and avoid false setup and system deterioration. In this study, we developed a simulation model as well as a visualisation of a disk-type automatic tool changer (ATC) to assist with ATC mechanical design and PLC logic verifi cation. Our simulation model was based on an object-oriented modelling approach, and consisted of model blocks corresponding to essential components such as the motor, gear set, cam-follower, and proximity sensors. We tested the model in a real-time simulation that used the software component of an actual machine tool controller in the simulation loop to evaluate the real-time calculation performance and the feasibility in a real application such as logic and confi guration verifi cation. The results related to the feed drive motion with limit sensor action in the ATC turret operation showed that our approach was practical and met the real-time requirements. Keywords: automatic tool changer; object-oriented model; logic verifi cation; real-time simulation 1.Introduction Computer numerical control (CNC) machine tools are composed of a variety of complex elements such as the feed drive, spindle, automatic tool changer (ATC), automatic pallet changer (APC), computer numerical controller, and programmable logic controller (PLC). Because of this, the design, construction, and setup is a complex and time-consuming process. A typical machining centre has several essential discrete systems such as the ATC, the APC, and guard doors. These subsystems play important roles in machine tool operations and machining automation. As a result, any performance improvement in the discrete systems can drastically increase the productiv- ity. However, the system confi guration, sequential logic generation, and verifi cation all still require considerable skill and are treated on a case by case basis because the process does not have eff ective verifi cation methods or environments. Simulation techniques have been successfully em- ployed in many industries to improve product quality and reduce development cycle time. In the machine tool industry, many types of simulation such as the fi nite element method (FEM) for machine tool frames, for example, are used in the development and manage- ment of machine tools. In this context, a verifi cation environment based on simulation could improve the system performance, reduce ramp-up time and cost, and avoid false setup and system deterioration. Various approaches are used to control or simulate discrete systems such as production lines. The typical and most prevalent method uses a Petri Net (David and Alla 1994). In an exemplary study, Lee and Hsu (2005) proposed a simplifi ed Petri Net controller, which included sensor status information to simplify process modelling at the controller design level. In their research on the design of ATC mechanisms, Go kler and Koc (1997) designed an automatic disk- type tool changer for a horizontal CNC machining centre, and Dereli and Filiz (2000) proposed a genetic algorithm-based optimisation method for the index position of a cutting tool on an ATC. In addition, Baykasoglu and Dereli (2004) presented a meta- heuristic optimisation system to determine the optimal index position of cutting tools for minimising the indexing time of the tool magazine on a CNC machine tool. While most of the existing research on ATCs has focused on determining the index position on tool magazines, a substantial amount of research has been devotedtomachinetoolsimulationandvirtual machinetools.ErkorkmazandAltintas(2001) *Corresponding author. Email: dwchopostech.ac.kr International Journal of Computer Integrated Manufacturing Vol. 21, No. 8, December 2008, 885894 ISSN 0951-192X print/ISSN 1362-3052 online ? 2008 Taylor these intercommunicate through shared memory. The controller library was composed of a numerical control (NC) kernel to control the feed drive system and a PLC kernel for operation of the discrete systems such as the limit sensor and ATC turret. The simulation model included the feed drive andATC turret modelsdescribed in section 3. We monitored the simulation results using a separate computer to avoid aff ecting the real-time performance ofthecomputerrunningthesimulationloop. The connection between the controller software and the simulationmodelwasidenticaltothatbetween the controller and the actual feed drive in the ATC turret except that the actual wiring was replaced by internal data communication. The proposed simula- tion was conducted on an industrial personal computer (NI PXI-8186 RT) with real-time kernel, a 2.2 GHz Pentium 4 CPU, and 512 MB of random access memory. We used a fourth-order RungeKutta algo- rithm with an integration time step of 0.5 ms for the simulation. The controller update time was set to 1 ms for the feed drive and 4 ms for the ATC turret. Figures 11(a) and (b) show the user interface of the real-time simulation for the feed drive system with a limit sensor and the ATC turret, respectively. Figure 10.Schematic diagram of a real-time simulation. Figure 11.Real-time simulation environment. 892Y.H. Jeong et al. In Figure 11(a), the feed drive motion is stopped by the action of a limit sensor located at a position of 0.5 m from the origin. The actual calculation time for 0.922 s of motion was 0.030 s, corresponding to better than 3000% of the real-time speed when synchronisation with an actual time base was disabled. In the ATC turret simulation, the PLC logic operates the ATC turret model using the sensor signals just as an actual PLC does. Figure 11(b) shows a snapshot during the simulation. When synchronisation with an actual time base was disabled, the actual calculation time of ATC turret operation during 0.241 s of motion was 0.0046 s, which corresponded to better than 5200% of the real- time speed. Wedesignedathree-dimensionalvisualisation moduletovisualizethesimulationresults. Figures 12(a) and (b) show the visualisation module consisting of a three-axis feed stage, a simple turret magazine, and a status board. The turret magazine showninthe fi gurehas14pallets.Thesignal board shows the sensor and operational status such as over-travel, current tool number, proximity sensor outputs, and homing results, i.e. typical discrete system information. 5.Conclusions In this study, we developed a simulation model of an automatic tool changer using a turret magazine. We used an object-oriented method to build a generalised model in which the essential components of the ATC turret were modelled as individual blocks, and then connected together as they would be in an actual ATC. Each block had its own parameters and equations that kinematically described the motion of the correspond- ing block. Thesimulationresultsdemonstratedthatthe proposed method generated realistic operations for component motions and sensor signals. We developed a three-dimensional visualisation to demonstrate the simulation results. The integration of our simulation model with the actual machine tool controller showed that our model could be used for the real-time logic verifi cation to reduce ramp-up time and false setup problems. In the real-time simulation of the PLC logic, the model successfully played the role of the real ATC turret and feed drive. We demonstrated that our models could satisfy real-time requirements, and the calculation time was less than 1/30th of the simulation loop time. Acknowledgement This study was supported by grant no. KRF-2004-202- D00068 from the Ministry of Science and Technology. References Baykasoglu, A. and Dereli, T., 2004. Heuristic optimization system for the determination on index positions on CNC magazines with the consideration of cutting tool duplica- tions. International Journal of Production Research, 42 (7), 12811303. Bru ck, D., et al., 2002. Dymola for multi-engineering modeling and simulation. In: 2nd International Modelica Conference, 55.155.8. David, R. and Alla, H., 1994. Petri nets for modeling of dynamic systemsa survey. Automatica, 30 (2), 175202. Dereli, T. and Filiz, _I.H., 2000. Allocating optimal index positions on tool magazines using genetic algorithm. Robotics and Autonomous Systems, 33, 155167. Erkorkmaz, K. and Altintas, Y., 2001. High speed CNC system design. Part II: modeling and identifi cation of feed drives. International Journal of Machine Tools and Manufacture, 41, 14871509. Go kler, M.L. and Koc , M.B., 1997. Design of an automatic tool changer with disc magazine for a CNC horizontal machining center. International Journal of Machine Tools and Manufacture, 37 (3), 277286. Figure 12.Visualisation module for the simulation results. International Journa